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There is overwhelming evidence on SARS-CoV-2 Airborne Transmission (AT) inthe ongoing COVID-19 outbreak. It is extraordinarily difficult, however, todeduce a generalized framework to assess the relative airborne transmissionrisk with respect to other modes. This is due to the complex biophysicsentailed in such phenomena. Since the SARS outbreak in 2002, ComputationalFluid Dynamics (CFD) has been one of the main tools scientists used toinvestigate AT of respiratory viruses. Now, CFD simulations produce intuitiveand physically plausible colour-coded results that help scientists understandSARS-CoV-2 airborne transmission patterns. In addition to validationrequirements, for any CFD model to be of epistemic value to the scientificcommunity; it must be reproducible. In 2020, more than 45 published studiesinvestigated SARS-CoV-2 airborne transmission in different scenarios using CFD.Here, I systematically review the published CFD studies of COVID-19 and discusstheir reproducibility criteria with respect to the CFD modeling process. Usinga Weighted Scoring Model (WSM), I propose a novel reproducibility index for CFDsimulations of SARS-CoV-2 AT. The proposed index $(0 \leq R^{CFD}_j \leq 1)$relies on three reproducibility criteria comprising 10 elements that representthe possibility of a CFD study (j) to be reproduced. Frustratingly, only 3 of23 studies (13%) achieved full reproducibility index $(R^{CFD}_j\geq 0.9)$while the remaining 87% were found generally irreproducible $(R^{CFD}_j<0.9)$.Without reproducible models, the scientific benefit of CFD simulations willremain hindered, fragmented and limited. In conclusion, I call the scientificcommunity to apply more rigorous measures on reporting and publishing CFDsimulations in COVID-19 research.

Amicus Plato, sed magis amica veritas: There is a reproducibility crisis in COVID-19 Computational Fluid Dynamics studies